Binary Simulation Data

This is an example of output from a simulation study that investigates the operating characteristics of inverse probability weighted Bayesian dynamic borrowing for the case with a binary outcome. This output was generated based on the binary simulation template. For this simulation study, only the degree of covariate imbalance (as indicated by population) and the marginal treatment effect were varied.

binary_sim_df

Format

binary_sim_df A data frame with 255 rows and 6 columns:

population

Populations defined by different covariate imbalances

marg_trt_eff

Marginal treatment effect

true_control_RR

True control response rate on the marginal scale

reject_H0_yes

Probability of rejecting the null hypothesis in the case with borrowing

no_borrowing_reject_H0_yes

Probability of rejecting the null hypothesis without borrowing

pwr_prior

Vector of power priors (or some other informative prior distribution for the control marginal parameter of interest based on the external data) as distributional objects